W3C Community Group: https://www.w3.org/community/pm-kr/ Published: February 20, 2026 Status: OPEN for participation
Develop open standards for storing knowledge as executable procedures (like font programs or mathematical formula definitions) with symlink-style composition, enabling both humans and AI systems to consume the same procedural source.
Core Problem: Current knowledge representation systems suffer from massive duplication and fragmentation. The same knowledge (e.g., a Unicode character, mathematical symbol, or spatial concept) is duplicated across fonts, embeddings, accessibility metadata, and visual renderings. This creates maintenance, performance, security, and licensing issues.
PM-KR Solution: Knowledge stored once as executable procedures, referenced via symlink-style composition (like Debian's APT package system), enabling:
- 70% compression (zero duplication)
- Dual-client reality (same procedural source → human visual + AI executable)
- Sovereign execution (zero external dependencies in runtime hot path)
- Multi-modal accessibility (visual, semantic, tactile, auditory from single source)
These documents establish the scope, technical depth, and biological inspiration for PM-KR:
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- 103+ cross-disciplinary connections spanning 586 years (1440-2026)
- 22 synthesis chains: Operating systems, GPU computing, typography, game industry, robotics, neuroscience, accessibility, video compression, carbon impact, philosophy
- Rarity estimate: Top 0.001-0.01% (1 in 10,000 to 1 in 100,000) for cross-disciplinary synthesis at this scale
- Why it matters: Shows PM-KR builds on giants' shoulders while contributing unique architectural innovations
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KNOWLEDGEVERSE_SPECIFICATION.md
- 7-region unified VRAM architecture: Cranium (reasoning), Galaxy Universe (active memory), House Universe (persistent memory), TRM (routing), Audit Journal, Routing Metadata, I/O Buffers
- Sovereign execution: PTX-only hot path, zero numpy/cupy/scipy/torch
- Persistent memory: Unified context across tasks (Grammar Galaxy grows during use)
- Why it matters: Technical foundation for procedural knowledge representation
-
ROBOTIC_EMBODIMENT_SPECIFICATION.md
- Hippocampus-inspired spatial memory: Biological precedent for PM-KR architecture
- Hardware-agnostic avatar: Human VR, AI agent, or physical robot use same code
- Form→Meaning bridge: Sensors (FORM) → Galaxy (MEANING) → RPN (ACTION)
- Zero robot-specific training: "Same architecture, different actuators"
- Why it matters: Shows biological grounding and practical applications beyond traditional knowledge graphs
This work is motivated by prior work on Knowledge3D, which serves as the reference implementation for PM-KR concepts.
Important: That work does not constrain the group's discussions, nor will it be a deliverable of this group. We welcome alternative implementations and approaches!
| Repository | Purpose | Status | Link |
|---|---|---|---|
| Knowledge3D | Reference implementation, production system | Active development | GitHub |
| pm-kr (this repo) | Open standards, specifications, test suites | Standards track | W3C CG |
Think of it like:
- WebKit/Chromium → standards-compliant browser implementations
- W3C HTML/CSS specs → open standards everyone can implement
- Knowledge3D is the browser; pm-kr is the spec
- Jonathan DeRouchie → Persistent memory AI architecture, public/private knowledge separation
- Nitin Pasumarthy (LinkedIn LLM/GNN) → Production-scale systems perspective
- Hanna Abi Akl (INRIA) 🇫🇷 → Neuro-symbolic AI, officially representing Institut National de Recherche en Informatique et en Automatique (French national research institute for computer science and automation)
- OpenFn Organization → Real-world validation (40+ countries, 10M+ transactions/year)
- Marko Rodriguez (Apache TinkerPop founder, Gremlin creator) → Graph traversal expertise, repository collaborator
- Milton Ponson (Mathematician) → Godelian critique of LLM scaling, Domains of Discourse
- José Vázquez-Jaramillo (Philosopher) → Epistemology and philosophical grounding
- Damir Cavar (Indiana University) → Computational linguistics, AI energy efficiency, Quantum AI, NLP (20+ years)
- Henrique Santos (RPI/Tetherless World Constellation) → Director of Semantic Applications, DARPA Machine Common Sense, knowledge graphs + LLMs
- Anisa Rula (University of Brescia) 🇮🇹 → CO-AUTHOR OF THE KNOWLEDGE GRAPHS BOOK (Springer 2021), KG quality & validation expert, Linked Data quality, data profiling
- Oserebameh Beckley → WebGPU compute shaders expert, GPU memory management, ray tracing, graphics programming (Medium technical writer)
- Majid Babaei (McGill University) 🇨🇦 → AI explainability via knowledge graphs, LLMs & AI agents research, Software Engineering (6 funded research internships May-Oct 2026, top-tier publications: ICSE, ICPE, MODELS)
- Charles Waweru → W3C Meta-Layer Infrastructure CG supporter, contextual annotation & semantic overlays, Web Annotation standards, layering interpretable meaning on existing content, decentralized civic infrastructure
- Rensselaer Polytechnic Institute (Tetherless World Constellation - world's top knowledge graph center, led by Deborah McGuinness)
- Indiana University (Computational linguistics program, founded by Damir Cavar)
- University of Brescia 🇮🇹 (Knowledge graph validation, semantic web research)
- LinkedIn (Production-scale GNNs)
- Digital Bazaar (Semantic Web technologies)
- INRIA 🇫🇷 (Institut National de Recherche en Informatique et en Automatique - French national research institute for computer science, Hanna Abi Akl - neuro-symbolic AI)
- McGill University 🇨🇦 (Majid Babaei - AI explainability, LLM/AI agent research)
Sovereign GPU-Native Execution: PM-KR demonstrates PTX (CUDA) kernels with zero external dependencies, showing GPU-first knowledge representation patterns relevant for WebGPU compute shaders.
3D Spatial Knowledge Navigation: Semantic proximity = spatial proximity in 3D workspace. Hippocampus-inspired architecture enables humans and AI to navigate knowledge spatially.
Procedural Typography & Math Symbols: 2,713 fonts stored as procedural programs (168,206 glyph-text pairs), mathematical symbols as RPN templates. One procedural source → multiple client modalities.
Procedural Execution Audit Trail: Audit Journal traces every procedural execution: "at point X during procedure Y, observed Z." Bridges observability and explainability.
Extreme Compression & Carbon Impact: 200:1 to 1000:1 compression via procedural canonicalization. Projected 2.2 Gt CO₂e/year savings by 2035 (6% global emissions).
Sovereign Audit + Decentralized Trust: Zero external dependencies aligns with decentralized identity. Procedural canonicalization enables content-addressed knowledge with cryptographic provenance.
Procedural Canonicalization: Complements RDF/JSON-LD with executable semantics. Symlink-style composition reduces knowledge graph redundancy while preserving semantic fidelity.
Spatial Knowledge in XR: Extends glTF's extras.k3d field for spatial knowledge in 3D assets. Dual-client reality where humans (VR) and AI (Galaxy) navigate same workspace.
Multimodal Accessibility from Single Source: Procedural sources render as visual glyphs, semantic descriptions, tactile patterns, all from same canonical procedure. No dual-maintenance overhead.
AI Knowledge Representation Integration: Explainability, sovereignty, multi-modal reasoning. Symlink composition (not black-box embeddings), zero external dependencies, auditable procedural sources.
Graph Compression + Procedural Execution: Procedural canonicalization stores graph patterns as reusable procedures. Collaboration with Apache TinkerPop founder brings graph traversal expertise.
Hippocampus-Inspired Architecture: Spatial memory mirrors biological hippocampus (episodic memory, spatial mapping, memory consolidation). Same spatial substrate for temporary reasoning + long-term knowledge.
Even before the official PM-KR launch, deep technical discussions with founding members have shaped the group's direction:
Key Insight: "Users are more likely to adopt a framework that uses or simplifies existing language, concept or structure."
Contributions:
- Form→Meaning Framework: Recognized that K3D mirrors 40,000 years of human knowledge evolution (cave paintings → letters → words → grammar → philosophy)
- Familiar Technical Labels: Recommended mapping K3D concepts to universal terms (tree, node, file system, OOP, graph database, 3D modeling)
- Multiple Mental Models: Proposed explaining K3D through multiple lenses:
- File System: House = directories, Rooms = folders, Objects = files
- OOP: Classes, inheritance, procedural composition
- Graph Database: Gremlin-style traversal (with Marko Rodriguez collaboration)
- 3D Modeling: Blender/Maya/Unity analogy (scenes, objects, materials, animation)
Impact: Led to Track 6 proposal for Year 1: "Developer Adoption & Cognitive Load Minimization"
- Familiar Technical Labels Mapping
- Multiple Mental Models Guide (file system, OOP, graph DB, 3D modeling)
- Getting Started for Different Roles (designers, devs, PMs)
- Gremlin → K3D Migration Guide
Key Insight: "Based on your interest in spatial approaches, I assume you've also studied the hippocampus?"
Biological Grounding:
- Hippocampus Connection: Validated K3D's biological inspiration (spatial navigation, episodic memory, memory consolidation)
- Computational Analogue: K3D House Universe mirrors hippocampus functions (place cells → 3D rooms, memory consolidation → SleepTime protocol)
Technical Contributions:
- Execution State Embeddings: Predicted (and K3D already implements!) 768-dim vectors encoding procedural state + semantic context
- Incremental Validation: "At point X during procedure Y, is candidate action A_i correct, efficient, safe, and ethical?"
- Faith Engine: K3D's 0.70 confidence threshold for safety validation
- Audit Message Schema: "at point X during Y, observed Z" (credited to Adam in PM-KR spec)
- OpenTelemetry Mapping: Traces, spans, context propagation for procedural execution
Track 5 Proposal: "Ethics & Safety for AI Agents and Robots"
- Multi-agent coordination via Galaxy Universe (centralized trusted resource)
- Safety predicates in procedural forms (MUST/MUST NOT constraints)
- Policy compliance validation (building on his Schema.org work, GitHub #4569)
- Structured validation reports for audit compliance
Multimodal Narrative Vision:
- Natural language narration (Galaxy introspection mode)
- Procedural video generation (K3D-VID, 200:1 compression)
- 3D visualization (humans walk through robot's "memory palace")
- Structured audit trail (machine-verifiable + human-readable)
Role: Apache TinkerPop founder, Gremlin creator, Knowledge3D repository collaborator
Contribution:
- Gremlin → K3D Mapping: K3D Galaxy navigation = 3D graph traversal (extends Gremlin concepts to spatial reasoning)
- Familiar Technical Concept: Gremlin is industry-standard (DataStax, Neo4j, major graph databases)
- Validation: Ensures K3D builds on established graph theory, not inventing unfamiliar abstractions
Connection:
Gremlin (2D graph traversal) → K3D Galaxy (3D graph traversal)
Graph nodes → K3D Nodes (stars in 3D space)
Graph edges → Semantic proximity (spatial distance)
g.V().has('name','X') → galaxy.query(embedding, top_k=10)
Track 1: OpenFn Integration Architecture (production validation) Track 2: BPMN → PM-KR Compilation Strategy (workflow verification) Track 3: State/Context Ontology (Adam's audit schema) Track 4: Lean4 Formalization (theorem proving for correctness) Track 5: Ethics & Safety for AI Agents/Robots (Adam's proposal) Track 6: Developer Adoption & Cognitive Load (Jonathan's proposal)
- THREE_BRAIN_SYSTEM_SPECIFICATION.md — Cranium + Galaxy + House architecture
- DUAL_CLIENT_CONTRACT_SPECIFICATION.md — Form→Meaning evolution (40,000 years)
- MATH_CORE_SPECIFICATION.md — 3-tier sovereign architecture example
- Complete Vocabulary Index
- PM_KR_PROBLEM_STATEMENT.md — Why PM-KR? (70%+ knowledge duplication crisis)
- PM_KR_NORMATIVE_MODEL.md — RFC 2119 compliant specification
- PM_KR_CONFORMANCE_PROFILES.md — Level A/B/C implementation requirements
- PM_KR_INTEROPERABILITY_GUIDE.md — RDF/OWL/JSON-LD bidirectional mapping
- Knowledge3D — A Universe of Meaning (6 min) — Perfect for W3C PM-KR members
- Multi-Language Playlist — 12 languages (English, Portuguese, Spanish, French, German, Italian, Mandarin, Japanese, Korean, Russian, Hindi, Arabic)
- NotebookLM Research Space — Best place to explore Knowledge3D/PM-KR in depth
- Visit: https://www.w3.org/community/pm-kr/
- Create W3C account (free): https://www.w3.org/accounts/request
- Join the group (no membership fees, open participation)
- Review specifications and share feedback
- Propose use cases from your domain (accessibility, XR, knowledge graphs, AI, robotics, spatial data, GPU computing, performance, trust)
- Participate in interoperability studies (RDF/OWL/JSON-LD mapping, WebGPU integration, glTF extensions)
- Help shape conformance levels and test suites
- Explore procedural canonicalization patterns
- Test bidirectional mapping (RDF ↔ PM-KR, glTF ↔ PM-KR)
- Validate compression claims (200:1-1000:1 ratios)
- Contribute sovereign execution patterns (zero external dependencies)
- ✅ Community Group published and open
- ✅ Phase 1 foundation documents available
- ✅ World-class experts participating
- ⏳ First working sessions upcoming
- Public comment period, gather use cases
- First collaborative working sessions
- Interoperability studies (RDF/JSON-LD mapping, WebGPU integration, spatial data standards)
- Draft specifications (data models, execution semantics, audit journal, conformance levels)
- Test suites and validation frameworks
- Reference implementations beyond Knowledge3D
- Data model specification (procedural composition, symlink references, content-addressing)
- Execution semantics (dual-client rendering, canonical procedures, sovereign runtime)
- Audit & tracing specification (temporal metadata, provenance, explainability)
- Compression guidelines (procedural canonicalization, carbon impact assessment)
- Interoperability guidelines (RDF/OWL/JSON-LD, WebGPU compute, glTF extensions, Trace Context)
- Accessibility specification (multimodal rendering from procedural sources)
- Use case documentation (accessibility, XR, knowledge graphs, AI systems, robotics, spatial data)
"We patent nothing. We publish everything. We build in the open."
- No patents: Apache 2.0 license for all contributions
- Public mailing lists: Transparent decision-making
- Open collaboration: Alternative implementations welcomed
- Cross-domain impact: Work benefits accessibility, XR, knowledge graphs, AI, robotics, spatial data, performance, trust—simultaneously
Mailing List (once launched): public-pm-kr@w3.org GitHub: https://github.com/w3c-cg/pm-kr W3C Page: https://www.w3.org/community/pm-kr/ Reference Implementation: https://github.com/danielcamposramos/Knowledge3D
Questions? Email: daniel@echosystems.ai
- Ian Jacobs (W3C Head of Communications) → PM-KR CG launch, editorial guidance
- Gutenberg Press (1440) → Democratized knowledge
- Aaron Swartz → Guerrilla Open Access Manifesto, open knowledge philosophy
- Tim Berners-Lee → Giant Global Graph vision, Semantic Web
- Nikola Tesla → 3-6-9 sacred geometry, ternary logic inspiration
- NVIDIA → CUDA, PTX ISA
- W3C Semantic Web Community → RDF, OWL, JSON-LD foundations
- Game Industry → glTF, spatial rendering, procedural generation
- Unicode Consortium → Character representation standards
- Khronos Group → Vulkan, OpenGL, GPU standards
Complete Attributions: Knowledge3D ATTRIBUTIONS.md
Built with collective intelligence. Shared with open hearts. For a sovereign, spatial future. ✨
pm-kr/
├── README.md # This file
├── CONTRIBUTING.md # Contribution guidelines (TBD)
├── CODE_OF_CONDUCT.md # W3C Code of Conduct
├── LICENSE # W3C Community Group License
├── specifications/ # Draft specifications (collaborative)
│ └── (TBD - group will develop together)
├── use-cases/ # Use case documentation
│ └── (TBD - contributions welcome)
├── interoperability/ # Interop studies and mappings
│ └── (TBD - RDF/JSON-LD/glTF mappings)
└── tests/ # Test suites and validation
└── (TBD - conformance tests)
Note: This repository structure will evolve as the group develops specifications collaboratively. For now, all technical documentation lives in Knowledge3D as the reference implementation.
Ready to help build the future of knowledge representation? Join us! 🚀